For Chinese paper charts, no standards are made yet, quality of paper charts are controlled by "there-level inspection" with naked eyes at present. This method has many disadvantages like more errors, more omissions, low efficiency and resource wastes etc. But paper charts can not be totally replaced by electronic charts in a short time. Thus, the research on new quality inspection method for paper charts in digital age is absolutely necessary. Aiming at the production of paper charts in digital environment, a new quality inspection method based on entity rules and cartographic specifications is put forward in this paper. Firstly, considering the fact that updating speed of charts database is closely related to the changing speed of maritime objects, each category of maritime features are analyzed from different aspects including their attributes, symbols, entity rules, changing features, etc. Based on this, features are classified into three categories according to their changing features to make sure that proper quality inspection method will be applied to certain features. The three categories are as follows: low changing speed, fast changing speed with regulations, fast changing speed without regulations. At the same time, rules of each feature and its relationships with some other features are analyzed, too, for all those changing speed and rules, relationships are the most important factors when design inspection methods for each kind of features. Secondly, the concept of inspection method based on entity rules and cartographic specifications are introduced.
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Aiming at sub-network division of GNSS continuous stations in TEONET (Tectonic and Environmental Observation Network in China), we design three schemes to process the data from doy 110 in 2010 to doy 103 in 2013. The first scheme (referred as regional scheme) has six regional sub-networks and each sub-network includes 55 GNSS permanent stations. The second scheme (named large-net scheme) has three sub-networks and each has 100 stations selected evenly in mainland China. The third scheme (named small-net scheme) has eight sub-networks and each has 55 stations selected evenly. Meanwhile, we analyze the differences between the results including station coordinates, horizontal velocity field and baseline length. The results show that the differences are within the current observation and calculation precision. From the above-motioned results and considering other factors such as computing time, we discuss the selection of sub-network division schemes in TEONET.
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Existing methods to quantitatively evaluate the performance of image-based 3D reconstruction are generally based on ground-truth 3D models acquired by 3D scanner, with disadvantages of high cost, low efficiency, and inapplicability to large-scale objects or scenes. To solve this problem, propose an evaluation method based on the invariance of image's phase information. Firstly, get the 2D projection image of the 3D reconstructed model under certain viewpoint. Then, extract edges of this projection image as well as the image of realistic object under the similar viewpoint. Subsequently, compute the proposed phase moment invariants for the two edge images and construct feature vectors. Finally, assess the reconstructed result through comparing the distance between the two feature vectors. Experiments validate the effectiveness and applicability of this method for assessing 3D reconstructed surface model.
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